code: def test_9a_keras_mnist(self):
      classifier = get_image_classifier_kr()
  
      scores = classifier._model.evaluate(
          self.x_train_mnist, self.y_train_mnist
      )
      logger.info(
          "[Keras, MNIST] Accuracy on training set: %.2f%%",
          scores[1] * 100,
      )
      scores = classifier._model.evaluate(
          self.x_test_mnist, self.y_test_mnist
      )
      logger.info(
          "[Keras, MNIST] Accuracy on test set: %.2f%%", scores[1] * 100
      )
  
      self._test_backend_mnist(
          classifier,
          self.x_train_mnist,
          self.y_train_mnist,
          self.x_test_mnist,
          self.y_test_mnist,
      )
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import logging
  import unittest
  import numpy
  import tensorflow
  from art.attacks.evasion.projected_gradient_descent.projected_gradient_descent import ProjectedGradientDescent
  from art.attacks.evasion.projected_gradient_descent.projected_gradient_descent_numpy import ProjectedGradientDescentNumpy, ProjectedGradientDescentCommon
  from art.estimators.classification import KerasClassifier
  from art.estimators.estimator import BaseEstimator, LossGradientsMixin
  from art.utils import get_labels_np_array, random_targets
  from tests.attacks.utils import backend_test_classifier_type_check_fail
  from tests.utils import TestBase, get_image_classifier_kr, get_image_classifier_pt, get_image_classifier_tf, get_tabular_classifier_kr, get_tabular_classifier_pt, get_tabular_classifier_tf, master_seed
label_desc: Use image node_id 2 for calling the TestPGD obj's underlying member method code with example usage: obj.test_9a_keras_mnist() without return types